mlsanityData to 14 Oct 2026

Inversion of Time-Lapse Surface Gravity Data for Detection of 3D CO2 Plumes via Deep Learning

arXiv 2209.02850 ↗First posted 6 Sep 2022cs.LG physics.geo-phcited by 3

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Abstract (arXiv)

We introduce three algorithms that invert simulated gravity data to 3D subsurface rock/flow properties. The first algorithm is a data-driven, deep learning-based approach, the second mixes a deep learning approach with physical modeling into a single workflow, and the third considers the time dependence of surface gravity monitoring. The target application of these proposed algorithms is the prediction of subsurface CO2 plumes as a complementary tool for monitoring CO2 sequestration deployments. Each proposed algorithm outperforms traditional inversion methods and produces high-resolution, 3D subsurface reconstructions in near real-time. Our proposed methods achieve Dice scores of up to 0.8 for predicted plume geometry and near perfect data misfit in terms of μGals. These results indicate that combining 4D surface gravity monitoring with deep learning techniques represents a low-cost, rapid, and non-intrusive method for monitoring CO2 storage sites.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 17 of its 61 references that are in the map. First posted on arXiv 6 Sep 2022.

Builds on

17 of 61 references.

References · 17

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5 more
  1. 2019Deep-Learning Inversion of Seismic Datacited by 32
  2. 2021Unsupervised Learning of Full-Waveform Inversion: Connecting CNN and Partial Differential Equation in a Loopcited by 29
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Citing papers per year: 2023: 2; 2024: 0; 2025: 1.

3 papers.

  1. 2023Solutions to Elliptic and Parabolic Problems via Finite Difference Based Unsupervised Small Linear Convolutional Neural Networkscited by 2
  2. 2023Joint inversion of Time-Lapse Surface Gravity and Seismic Data for Monitoring of 3D CO2 Plumes via Deep Learningcited by 1
  3. 2025Learning Discontinuous Galerkin Solutions to Elliptic Problems via Small Linear Convolutional Neural Networkscited by 1